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Wealth Dynamics and a Bias Toward Momentum Trading

  • Blake LeBaron

    ()

    (International Business School, Brandeis University)

Evolutionary metaphors have been prominent in both economics and finance. They are often used as basic foundations for rational behavior and efficient markets. Theoretically, a mechanism which selects for rational investors actually requires many caveats, and is far from generic. This paper tests wealth based evolution in a simple, stylized agent-based financial market. The setup borrows extensively from current research in finance that considers optimal behavior with some amount of return predictability. The results confirm that with a homogeneous world of log utility investors wealth will converge onto optimal adaptive forecasting parameters. However, in the case of utility functions which differ from log, wealth selection alone converges to parameters which are economically far from the optimal forecast parameters. This serves as a strong reminder that wealth selection and utility maximization are not the same thing. Therefore, suboptimal financial forecasting strategies may be difficult to drive out of a market, and may even do quite well for some time.

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File URL: http://www.brandeis.edu/departments/economics/RePEc/brd/doc/Brandeis_WP14.pdf
File Function: First version, 2010
Download Restriction: no

Paper provided by Brandeis University, Department of Economics and International Businesss School in its series Working Papers with number 14.

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Length: 13 pages
Date of creation: Dec 2010
Date of revision:
Handle: RePEc:brd:wpaper:14
Contact details of provider: Postal: MS032, P.O. Box 9110, Waltham, MA 02454-9110
Web page: http://www.brandeis.edu/departments/economics/

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  1. Campbell, John & Viceira, Luis, 1999. "Consumption and Portfolio Decisions When Expected Returns are Time Varying," Scholarly Articles 3163266, Harvard University Department of Economics.
  2. Robert R. Bliss & Nikolaos Panigirtzoglou, 2004. "Option-Implied Risk Aversion Estimates," Journal of Finance, American Finance Association, vol. 59(1), pages 407-446, 02.
  3. Evstigneev, Igor V. & Hens, Thorsten & Schenk-Hoppé, Klaus Reiner, 2005. "Globally Evolutionarily Stable Portfolio Rules," Discussion Papers 2005/17, Department of Business and Management Science, Norwegian School of Economics.
  4. Hakansson, Nils H, 1971. "Multi-Period Mean-Variance Analysis: Toward A General Theory of Portfolio Choice," Journal of Finance, American Finance Association, vol. 26(4), pages 857-84, September.
  5. Pástor, Luboš & Stambaugh, Robert F., 2007. "Predictive Systems: Living with Imperfect Predictors," CEPR Discussion Papers 6076, C.E.P.R. Discussion Papers.
  6. J. Bradford De Long & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1988. "The Survival of Noise Traders in Financial Markets," NBER Working Papers 2715, National Bureau of Economic Research, Inc.
  7. Kogan, Leonid & Ross, Stephen & Wang, Jiang & Westerfield, Mark, 2003. "The Price Impact and Survival of Irrational Traders," Working papers 4293-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
  8. Robert F. Stambaugh, 1999. "Predictive Regressions," NBER Technical Working Papers 0240, National Bureau of Economic Research, Inc.
  9. Armen A. Alchian, 1950. "Uncertainty, Evolution, and Economic Theory," Journal of Political Economy, University of Chicago Press, vol. 58, pages 211.
  10. Larry Blume & David Easley, 2001. "If You're So Smart, Why Aren't You Rich? Belief Selection in Complete and Incomplete Markets," Cowles Foundation Discussion Papers 1319, Cowles Foundation for Research in Economics, Yale University.
  11. Blake LeBaron, 2011. "Active and Passive Learning in Agent-based Financial Markets," Eastern Economic Journal, Palgrave Macmillan, vol. 37(1), pages 35-43.
  12. Menkhoff, Lukas & Taylor, Mark P., 2006. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Hannover Economic Papers (HEP) dp-352, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
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